The following disclosure relates to three-dimensional X-ray cone-beam computed tomography for medical applications, wherein a plurality of X-ray projection images acquired from different angles are used to reconstruct 3-D cross-sectional images of an anatomy of a patient. The duration of the X-ray projection image acquisition is typically of the order of 10-30 seconds because the X-ray tube (X-ray source) and sensor (X-ray detector) must physically travel the spatial trajectory corresponding to the acquisition angles. The imaging trajectory is typically realized by a rotation and translation mechanism.
The imaging trajectory should be known with a sufficient accuracy and the imaged object should remain sufficiently stationary during the X-ray projection image acquisition in order for the reconstructed CBCT image to be sharp and true to the anatomy, because the projection image measurements are assumed to represent co-registered integrated views of a stationary object. This results in a set of geometrically consistent measurements that can be used to reconstruct the attenuation distribution representing the studied anatomy. Whenever these assumptions are violated, the accuracy of the reconstructed image is degraded as a consequence of the projection measurements becoming mutually inconsistent.
The accuracy of the final image typically depends on how accurately the assumptions made in the reconstruction process correspond to the actual, physical image acquisition process. The estimated spatial positions of the X-ray source and detector corresponding to each acquired X-ray image affect the computation of the ray paths during the CBCT reconstruction process. Due to inherent manufacturing and operating tolerances and potential deformation of the imaging device the realized rotation angles and positions tend to deviate from the ideal values according to the assumed form of the imaging trajectory. A systematic deviation, however, can be addressed by using different calibration methods that are repeated after certain period of time or operation cycles.
In medical CBCT imaging, the most significant source of geometric inaccuracy is the potential movement of the patient during the acquisition of the X-ray projection images. Namely, if the imaged object moves during the acquisition of the X-ray projection images, the effective spatial paths of the ray measurements become mutually inconsistent. Although it is well-known that the patient should not move and the patients are routinely instructed not to do so, a patient typically cannot remain completely stationary during the acquisition of the X-ray projections. This problem is typically addressed by supporting the patient. However, supporting the patient too tightly is inconvenient and uncomfortable. Furthermore, preventing all patient movement would require using a highly constraining support, which is not applicable in routine imaging.
In medical CBCT imaging both of the inaccuracies described above are present to some degree in all practical measurements. In a worst case scenario, the resulting geometric inconsistency of the projection image measurements may even require repeating the scan after a radiologist has inspected the quality of the image reconstruction. This is undesirable due to the radiation dose associated with the X-ray image acquisition, which is aimed to be kept as low as reasonably possible.
Computational approaches have been developed to address the problem of geometric inaccuracy in computed tomography imaging. In reported approaches in the literature, a virtual motion of the X-ray source and X-ray detector by means of a rigid geometric transformation in a fixed coordinate system has been applied to model and compensate for a rigid motion during the projection image acquisition. In recent approaches related to medical CBCT imaging, such geometric transformation is optimized by maximizing the sharpness of the resulting CBCT reconstruction. Typically such correction process is performed iteratively.
In CBCT imaging, applying a fixed coordinate system for the modelling and compensation of patient motion is not ideal, as the intrinsic geometric degrees-of-freedom in CBCT imaging are not separated by the coordinate system. In a CBCT imaging device, it is particular that the X-ray beams diverge and form a pyramid-shaped cone. As a result, a shift along the isoray adjoining the X-ray source and the center of the X-ray detector will only affect the magnification factor, whereas an in-plane shift along the X-ray detector's pixel array will result in a maximal shift of the imaged object within its projection image. Moreover, preventing a net transformation arising as a result of an applied geometric correction by known means of a rigid registration of the resulting corrected CBCT reconstruction and the uncorrected CBCT reconstruction is computationally expensive, especially if applied repeatedly during the geometric correction process.